%0 Journal Article
%A Suchan, Tomasz
%A Talavera, Gerard
%A Sáez, Llorenç
%A Ronikier, Michał
%A Vila, Roger
%T Pollen metabarcoding as a tool for tracking long-distance insect migrations.
%D 2018
%R 10.1101/312363
%J bioRxiv
%P 312363
%X Insects account for the main fraction of Earth's biodiversity and are key players for ecosystems, notably as pollinators. While insect migration is suspected to represent a natural phenomenon of major importance, remarkably little is known about it, except for a few flagship species. The reason for this situation is mainly due to technical limitations in the study of insect movement. Here we propose using metabarcoding of pollen carried by insects as a method for tracking their migrations. We developed a flexible and simple protocol allowing high multiplexing and not requiring DNA extraction, one of the most time consuming part of metabarcoding protocols, and apply this method to the study of the long-distance migration of the butterfly Vanessa cardui, an emerging model for insect migration. We collected 47 butterfly samples along the Mediterranean coast of Spain in spring and performed metabarcoding of pollen collected from their bodies to test for potential arrivals from the African continent. In total, we detected 157 plant species from 23 orders, most of which (82.8%) were insect-pollinated. African or African-Arabian endemic taxa contributed 21.0% of our dataset, strongly supporting the hypothesis that migratory butterflies colonize southern Europe from Africa in spring. Moreover, our data suggest that a northwards trans-Saharan migration in spring is plausible for early arrivals (February) into Europe, as shown by the presence of Saharan floristic elements. Our results demonstrate the possibility of regular insect-mediated transcontinental pollination, with potential implications for ecosystem functioning, agriculture and plant phylogeography. Despite current limitations, mostly regarding the availability of plant reference sequences and distribution data, the method proved to be useful and demonstrates great potential as plant genetic libraries and distribution datasets improve.
%U https://www.biorxiv.org/content/biorxiv/early/2018/05/02/312363.full.pdf